This core brings together three established teams for mouse imaging and orthotopic and genetically induced tumor models. It will not only provide the animal models but also in-vivo non-destructive imaging to detect tumors or devices. Providing animal models is essential for this Center grant as it includes investigators from the physical sciences with limited animal experience.The Core will be able to perform entire experiments for investigators. The Genetically Induced Murine Tumor Service staffed with trained personnel that provide all the needed services to study and/or image native breast tumors and leukemia in genetically susceptible mice. The Dept of Radiology and the Cancer Center at UCSD have established a Small Animal Imaging Resource (SAIR) to support cancer research. The dedicated rodent imaging facility (-650 sq.ft.) located adjacent to the vivarium houses optical, CT, PET and ultrasound imaging, as well as a high-resolution digital autoradiography and fluorescent imaging system for post-mortem analysis. The SAIR also provides rodent MRI on a 7T system located about one mile from the Cancer Center adjacent to another vivarium. Support and expertise include: imaging, animal care, image computation, MR &optical hardware and software, diagnostic agent chemistry, radiochemistry including cyclotron, analytical chemistry, kinetic modeling and parametric imaging, anatomic and histological confirmation. The imaging team is developing molecular imaging approaches to provide non-invasive biomarker detection, characterization and monitoring of tumors. There are three high priority goals for the imaging team: 1) Optimize image acquisition and blood sampling to enable kinetic modeling to better evaluate agent distribution;2) Co-register imaging data to post-mortem slices to provide accurate anatomic confirmation and accurate image-guided tissue sampling of regions of interest for further analysis;and 3) Complete automation of imaging data reduction for kinetic modeling including co-registration of the multiple volume acquisitions to accurately define the time-intensity-curve on a volumetric basis and the generation of parametric images to improve throughput and eliminate operator bias.